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Most of person Re-Identification (ReID) works extract features from the top CNN layer for person image matching. The top CNN layer commonly corresponds to large receptive fields, thus is not effective in depicting visual cues at multiple scales, e.g. , both global appearance and local details. This work proposes a Progressive Feature Enhancement (PFE) algorithm to spot and fuse multi-scale discriminative cues from different CNN layers into a single feature vector. The basic idea is to progressively learn complementary features with a layer-specific supervision from deep to shallow layers. The layer-specific supervision is inferred by the proposed Masked Feature Augmentation (MFA) module. For each CNN layer, MFA indicates cues that have been captured in its deeper layers. MFA hence supervises each layer to depict additional visual cues missed by its deeper layers. This framework effectively learns multi-scale features without requiring extra part annotations or dividing body parts. To further facilitate the layer-specific feature generation, a Two-Stage Attention Module (TSAM) is proposed to filter pixel-wise and channel-wise noises on intermediate feature maps. Extensive experiments on four ReID datasets show that our approach achieves competitive performance, e.g. , with ResNet50 backbone, it achieves rank1 accuracy of 95.1%, 88.2%, 79.1% and 71.6% on Market-1501 , DukeMTMC-ReID , MSMT17 and CUHK03 Detected , respectively, outperforming many state-of-the-art works.

Various factors like occlusions, backgrounds, etc., would lead to misaligned detected bounding boxes , e.g., ones covering only portions of human body. This issue is common but overlooked by previous person search works. To alleviate this issue, this paper proposes an Align-to-Part Network (APNet) for person detection and re-Identification (reID). APNet refines detected bounding boxes to cover the estimated holistic body regions, from which discriminative part features can be extracted and aligned. Aligned part features naturally formulate reID as a partial feature matching procedure, where valid part features are selected for similarity computation, while part features on occluded or noisy regions are discarded. This design enhances the robustness of person search to real-world challenges with marginal computation overhead. This paper also contributes a Large-Scale dataset for Person Search in the wild (LSPS), which is by far the largest and the most challenging dataset for person search. Experiments show that APNet brings considerable performance improvement on LSPS. Meanwhile, it achieves competitive performance on existing person search benchmarks like CUHK-SYSU and PRW., Comment: 9 pages, 7 figures, accepted to CVPR 2020. The dataset will be released soon

The special multi-scenario of the topology in the wireless hybrid ad hoc networks is studied in this paper. A new performance evaluation link cognitive cooperation air time metric (LCCATM) and a novel cross layer multicarrier MIMO cognitive cooperation scheme are proposed. The proposed scheme integrated the attributes both of the new performance evaluation of the cooperative diversity and the attributes of the topology space. With the help of the proposed scheme, the cooperative ability of the networks is not only cognitive, but also topology aware. The average achievable sum rates and the outage probability of the networks are all examined with the cross layer constraints. The simulation results show that the proposed scheme can enhance the average rate performance and make the outage probability stable.

We investigate the symbol error rate (SER) of the cooperative transmission with the decode-and-forward relay protocol under Rayleigh fading channels. The technique of orthogonal space-time block coding (OSTBC) is applied at the links source-relay, source-destination and relay-destination. A closed-form SER expression is derived. Simulation results demonstrate the theoretical solutions.

The multi-scenario topology of multi-channel hybrid ubiquitous sensor networks (USNs) is studied and a novel link auto-diversity cross-layer cooperative scheduling scheme is proposed in this paper. The proposed scheme integrates the attributes of the new performance evaluation link auto-diversity air-time metric and the topology space in the given multi-scenario. The proposed scheme is compared with other schemes, and its superiority is demonstrated through simulations. The simulation results show that relative energy consumption, link reception probability, and end-to-end blocking probability are improved. The addressing ratio of success with unchanged parameters and external information can be increased. The network can tolerate more hops to support reliable transportation when the proposed scheme is implemented. Moreover, the scheme can make the network stable. Therefore, the proposed scheme can enhance the average rate performance of the hybrid USN and stabilize the outage probability.

The special scenario of the topology in the cellular Ad Hoc networks is studied and a novel cross layer game knowledge sharing algorithm based on multi-hop routing Neural Fuzzy Connection Admission Controller (NFCAC) is proposed in this paper. NFCAC has been successfully applied in the control-related problems of neural networks. However, there is no discussion about the game knowledge sharing algorithm and location recognition based on NFCAC in cellular Ad Hoc networking. We firstly propose a novel multi-hop routing NFCAC which is suitable for cellular Ad Hoc networking and then propose the algorithm to integrate the functions of both multi-hop routing NFCAC and the topology space in the special scenario. The topology and power consumption of each Mobile Host (MH) can be optimized due to the minimum link occupation with the help of the algorithm. Simulation results show that the algorithm can give more control guarantee to the networks in the variable MH loads and transmission powers, and make the MHs stable to support multi-hops at the same time.

Link-adaptation scheme has been recognized as an effective way to improve the performance of energy efficiency of the IEEE 802.11a wireless local-area networks (WLANs). In this paper, we propose a new link-adaptation scheme for energy efficiency by dynamically adjusting the data transmission rate according to network load and channel quality. We first give an overview of the IEEE 802.11a orthogonal frequency domain multiplexing (OFDM) physical layer and the distributed coordination function (DCF) of the IEEE 802.11 MAC. Then, based on the theoretical goodput analysis, we proposed a new method to enhance the energy efficiency via optimizing the goodput performance using nonlinear optimization with constraints. Despite the nonlinearity in the objective function and the constraints, we show that the energy efficiency optimization can be efficiently solved for global optimality through a convex optimization technique. Our simulation results show that our link-adaptation scheme enhances the energy efficiency as well as the goodput performance of an IEEE 802.11a wireless LAN through dynamic frame length control, contention window (CW) selection, and PHY rate selection, depending on the wireless channel condition. Moreover, the proposed scheme can be extended to address some similar problems in other kinds of networks, such as congestion control, admission control, and power control.

We address the outage performance for the opportunistic amplify-and-forward relaying strategies under Nakagami-m fading channels. A closed-form expression for the outage probability is derived. Simulation results verify our theoretical solutions.

The performance of the implant inside a human body with polarisation, distance, and different power settings at the base-station is presented. In addition, the unslotted CSMA/CA protocol is studied for a heterogeneous WBAN.

The multi-scenario topology of the wireless hybrid Ad Hoc networks is studied and a novel Cross Layer Power Efficient Cooperative Diversity Scheme (CL-PECDS) is proposed in this paper. The comparison and the predominance of the proposed scheme are demonstrated. With the help of the simulations, the relative energy consumption and the end-to-end blocking probability are all improved. The addressing ratio of success in the condition of the unchanged parameters and external information can be increased and the network can tolerate more hops to support reliable transportation by the proposed scheme.

The dual-cross scenario of the hybrid wireless sensor networks (WSNs) is studied and a novel MIMO Cluster Cooperative Assignment Cross Layer Scheduling Scheme (MCCA-CLSS) is proposed in this paper. The comparison and the predominance of the proposed scheme are demonstrated, the clusters are optimized. With the help of the simulations, the relative energy consumption and the end-to-end blocking probability are all improved. The addressing ratio of success in the condition of the unchanged parameters and external information can be increased and the network can tolerate more hops to support reliable transportation by the proposed scheme., Comment: 4 figures, 9th International Symposium on Communication and Information Technology 2009 (ISCIT 2009), September 28-30, 2009, South Korea

IEEE 802.11 and IEEE 802.15.3 are wireless standards originally designed for wireless local area network (WLAN) and wireless personal area network (WPAN). This paper studies MAC throughput analysis of both standards. We present a comparative analysis of both standards in terms of MAC throughput and bandwidth efficiency. Numerical results show that the performance of IEEE 802.15.3 transcends IEEE 802.11 in all cases., Comment: 4 pages, 6 figures, 1 table, 4th International Conference on Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08

The multi-scenario of the topology in the hybrid ad hoc networks is studied and a novel cross layer resource scheduling scheme based on the topology is proposed in this paper. The proposed scheme integrated the attributes both of the new performance evaluation machine link resource check metric (MLRCM) and the topology space with the special multi-scenario. The power consumption of each node can be optimized due to the minimum resource occupation with the help of this scheme. Simulation results show that the proposed scheme can give power control guarantee to the multi-channel hybrid ad hoc networks in the variable node loads and transmission powers, and make the node stable to support multi-hops at the same time.

This work pays attention to the performance analysis of the conventional and encoded time hopping binary phase shift keying modulation (TH-BPSK) ultra wideband systems over multipath fading channels. In order to resist the multipath effects, selective diversity combining Rake (SRake) receiver is employed. The encoded TH-BPSK UWB system is obtained by substituting a convolutional encoder for the repetition encoder. Soft output Viterbi algorithm (SOVA) and Viterbi algorithm (VA) are employed as the decoding methods. The performance analysis shows that the coded TH-BPSK system outperforms the uncoded scheme significantly with the increase of the SRake receiver fingers. The effective order of processing gains achieved by the coded scheme is the product of the number of SRake branches and the free distance of the convolutional code.

In this paper, a novel code selected M-ary direct sequence ultra wideband communication system is introduced. The objective is to get a high data rate UWB system by using the M-ary coded selected direct sequence bipolar pulse amplitude modulation (MCSDS-BPAM) scheme. In this system, a particular DS code sequence can be selected by the log2(M/2) bits from the DS code set. This scheme can obtain high data rate without increasing the system bandwidth or changing the pulse shape. With the increase of the modulation level M, the system bit error rate (BER) will be improved for the same signal energy per bit. The simulation results are provided in the condition of AWGN channel and correlation receivers.

The special scenario of the topology in the IEEE 802.16-based multi-radio heterogeneous ad hoc networks was analyzed and a novel cross layer game algorithm based on neural fuzzy connection admission controller (NFCAC) was proposed in this paper. NFCAC has been successfully applied in the control-related problems of neural networks. However, there is no discussion about the power control game algorithm and location recognition based on NFCAC in heterogeneous ad hoc networks. The proposed algorithm integrated the attributes both of NFCAC and the topology space in special scenario. The topology and the power consumption of each node can all be optimized due to the minimum link occupation with the help of the algorithm. Simulation results show that the novel algorithm can give more power control guarantee to heterogeneous ad hoc networks in the variable node loads and transmitting powers, and make the node more stable to support multi-hops at the same time.

We address the outage performance in the Rayleigh fading for the decode-and-forward relaying with multiple receive antennas at the destination. A closed-form expression for the outage probability is derived. Simulation results demonstrate our theoretical solutions.

The special scenario of the topology in the hybrid multimedia Ad Hoc networks was analyzed and a novel cross layer Biomimetic Pattern Recognition (BPR) algorithm based on Neural Fuzzy Connection Admission Controller (NFCAC) was proposed. The novel algorithm integrated the attributes both of NFC AC and the topology space in special scenario. The topology and the power consumption of each node can all be optimized due to the minimum link occupation with the help of the algorithm. Simulation results shown that the novel algorithm can give more BPR guarantee to the networks in the variable node loads and transmitting powers, and make the node more stable to support multi-hops at the same time.

The special scenario of the topology in the cellular Ad Hoc networks was analyzed and a novel cross layer power control game algorithm based on Neural Fuzzy Connection Admission Controller (NFCAC) was proposed in this paper. NFCAC has been successfully applied in the control-related problems of neural networks. However, there is no discussion about the power control game algorithm and location recognition based on NFCAC in cellular Ad Hoc networks. The proposed algorithm integrated the attributes both of NFCAC and the topology space in special scenario. The topology and the power consumption of each node can all be optimized due to the minimum link occupation with the help of the algorithm. Simulation results show that the novel algorithm can give more power control guarantee to cellular Ad Hoc networks in the variable node loads and transmitting powers, and make the node more stable to support multi-hops at the same time.

This paper analyzed two topologies of self-organizing cellular neural networks based on a hybrid mode that combines IEEE 802.11g and 802.11a in different dimensions, and investigated the relationship between the attributes of the networks and the topology spaces. Then a novel scheme for the low delay marking (LDM) algorithm, called modified-low delay marking (M-LDM), is proposed. Performance analysis of the connectivity and other properties was conducted and shown that the proposed modification to the LDM algorithm can optimize the round trip time (RTT) and make the network more effective and more stable in the case of the special scenarios that were investigated, by modifying the patterns for neurons, optimizing the window size and adjusting the marking probability

This paper presents a new model based on Hopfield neural network (HNN) that solves the optimum routing problem for supporting QoS in Ad hoc networks. The model is based on the minimum cost under delay constraints in ad hoc network in order that the neural network could be robust to the changed of the network topology. Under this assumption the general principles involved in the design of the proposed neural network and the method regarding the relationships of different coefficients in the energy function are discussed. The computational power of the proposed neural model is demonstrated through computer simulations. Simulation results indicate that our proposed scheme is very effective and outperforms previous schemes.

In this paper, we propose a modified DSR protocol in special scenario and combined this protocol with location information. The location information gives each node local information rather than a global one in the routing of wireless ad hoc networks. The simulation results show that the modified protocol is more efficient than the traditional DSR in the two given scenarios.