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We propose a real-time DNN-based technique to segment hand and object of interacting motions from depth inputs. Our model is called DenseAttentionSeg, which contains a dense attention mechanism to fuse information in different scales and…
This paper studies the sensing base station (SBS) that has great potential to improve the safety of vehicles and pedestrians on roads. It can detect the targets on the road with communication signals using the integrated sensing and…
A brain-computer interface (BCI) facilitates direct interaction between the brain and external devices. To concurrently achieve high decoding accuracy and low energy consumption in invasive BCIs, we propose a novel spiking neural network…
Snoring is a common disorder that affects people's social and marital lives. The annoyance caused by snoring can be partially solved with active noise control systems. In this context, the present work aims at introducing an enhanced system…
Subnetworks are expected to enhance wireless pervasiveness for critical applications such as wireless control of plants, however, they are interference-limited due to their extreme density. This paper proposes a goal-oriented joint power…
In the conventional person Re-ID setting, it is widely assumed that cropped person images are for each individual. However, in a crowded scene, off-shelf-detectors may generate bounding boxes involving multiple people, where the large…
The performance of neural decoders can degrade over time due to nonstationarities in the relationship between neuronal activity and behavior. In this case, brain-machine interfaces (BMI) require adaptation of their decoders to maintain high…
This paper presents adaptive bidirectional minimum mean-square error parameter estimation algorithms for fast-fading channels. The time correlation between successive channel gains is exploited to improve the estimation and tracking…
In this paper we demonstrate the rate gains achieved by two-tier heterogeneous cellular networks (HetNets) with varying degrees of coordination between macrocell and microcell base stations (BSs). We show that without the presence of…
The march towards 6G is accelerating and future wireless network architectures require enhanced performance along with significant coverage especially, to combat impairments on account of the wireless channel. Reconfigurable intelligent…
Considering both non-line-of-sight (NLoS) and line-of-sight (LoS) transmissions, the transitional behaviors from noise-limited regime to dense interference-limited regime have been investigated for the fifth generation (5G) small cell…
The number of simultaneously recorded neurons follows an exponentially increasing trend in implantable brain-machine interfaces (iBMIs). Integrating the neural decoder in the implant is an effective data compression method for future…
The fifth generation of wireless communications (5G) promises massive increases in traffic volume and data rates, as well as improved reliability in voice calls. Jointly optimizing beamforming, power control, and interference coordination…
This paper investigates the idea of exploiting interference among the simultaneous multiuser transmissions in the downlink of multiple antennas systems. Using symbol level precoding, a new approach towards addressing the multiuser…
Wireless spiking neural networks (WSNNs) allow energy-efficient communications, especially when considering edge intelligence and learning for both terrestrial beyond 5G/6G and space networking systems. Recent research work has revealed…
Recent worldwide events shed light on the need of human-centered systems engineering in the healthcare domain. These systems must be prepared to evolve quickly but safely, according to unpredicted environments and ever-changing pathogens…
The sixth-generation (6G) wireless networks will rely on ultra-dense multi-cell deployment to meet the high rate and connectivity demands. However, frequency reuse leads to severe inter-cell interference, particularly for cell-edge users,…
Electroencephalography (EEG) provides a non-invasive window into brain activity, offering high temporal resolution crucial for understanding and interacting with neural processes through brain-computer interfaces (BCIs). Current dual-stream…
Efficient utilization of licensed spectrum in the cognitive radio network is challenging due to lack of coordination among the Secondary Users (SUs). Distributed algorithms proposed in the literature aim to maximize the network throughput…
Multi-regional interaction among neuronal populations underlies the brain's processing of rich sensory information in our daily lives. Recent neuroscience and neuroimaging studies have increasingly used naturalistic stimuli and experimental…