相关论文: Deep Learning Based Solar Cell Recognition for Opt…

Previous transfer learning methods based on deep network assume the knowledge should be transferred between the same hidden layers of the source domain and the target domains. This assumption doesn't always hold true, especially when the…

Transparent electronics offer exciting light harvesting solutions for generation of electrical power via demonstration of "see-through" optoelectronic devices. The wireless energy harvesting ability can empower unplugged and battery-free…

A Deep Belief Network (DBN) requires large, multiple hidden layers with high number of hidden units to learn good features from the raw pixels of large images. This implies more training time as well as computational complexity. By…

The increasing demands of power supply and data rate for mobile devices promote the research of simultaneous wireless information and power transfer (SWIPT). Optical SWIPT, as known as simultaneous light information and power transfer…

This paper presents a rigorous optimization technique for wireless power transfer (WPT) systems enhanced by passive elements, ranging from simple reflectors and intermedi- ate relays all the way to general electromagnetic guiding and…

Distributed denial-of-service (DDoS) attacks threaten the availability of Internet of Things (IoT) infrastructures, particularly under resource-constrained deployment conditions. Although transfer learning models have shown promising…

This study focuses on event detection in optical fibers, specifically classifying six events using the Phase-OTDR system. A novel approach is introduced to enhance Phase-OTDR data analysis by transforming 1D data into grayscale images…

A new line of research on communications and signals design for Wireless Power Transfer (WPT) has recently emerged in the communication literature. Promising signal strategies to maximize the power transfer efficiency of WPT rely on…

A near-field simultaneous wireless information and power transfer (SWIPT) network is investigated, where the hybrid beamforming architecture is employed at the base station (BS) for information transmission while charging energy harvesting…

Plant phenotyping focuses on the measurement of plant characteristics throughout the growing season, typically with the goal of evaluating genotypes for plant breeding. Estimating plant location is important for identifying genotypes which…

Intracavity laser-based systems are emerging as key enablers for next-generation wireless communications, positioning, and wireless power transfer (WPT). Distributed coupled-cavity laser (DCCL) systems, as a representative configuration,…

Recent approaches have shown that training deep neural networks directly on large-scale image-text pair collections enables zero-shot transfer on various recognition tasks. One central issue is how this can be generalized to object…

Light Fidelity (Li-Fi) is a networked version of optical wireless communication (OWC), which is a strong candidate to fulfill the unprecedented increase in user-traffic expected in the near future. In OWC, a high number of optical access…

In this paper, we implement an optical fiber communication system as an end-to-end deep neural network, including the complete chain of transmitter, channel model, and receiver. This approach enables the optimization of the transceiver in a…

This paper considers utility optimal power control for energy harvesting wireless devices with a finite capacity battery. The distribution information of the underlying wireless environment and harvestable energy is unknown and only…

Over the last two decades the organic solar cell community has synthesised tens of thousands of novel polymers and small molecules in the search for an optimum light harvesting material. These materials were often crudely evaluated simply…

We demonstrate a deep-learning-based fibre imaging system which can transfer real-time artifact-free cell images through a meter-long Anderson localizing optical fibre. The cell samples are illuminated by an incoherent LED light source. A…

Wireless sensor networks consist of randomly distributed sensor nodes for monitoring targets or areas of interest. Maintaining the network for continuous surveillance is a challenge due to the limited battery capacity in each sensor.…

The widespread adoption of depth sensors has substantially lowered the barrier to point-cloud acquisition. This letter proposes a semantic wireless transmission framework for three dimension (3D) point clouds built on Deep Joint Source -…

Transfer learning is a machine learning technique that uses previously acquired knowledge from a source domain to enhance learning in a target domain by reusing learned weights. This technique is ubiquitous because of its great advantages…