Quantum-Inspired Data Embedding for Unlabeled Data in Sparse Environments: A Theoretical Framework for Improved Semi-Supervised Learning without Hardware Dependence by Shawn Ray

“…In contrast to conventional quantum machine learning methodologies that often rely on quantum hardware, this framework is fully realizable within classical computational architectures, thus bypassing the practical limitations of quantum hardware. …”
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Autonomous Streaming Space Objects Detection Based on a Remote Optical System by V. S. Baranova, V. A. Saetchnikov, A. A. Spiridonov

“…But the speed of the computing architecture and the functions of small optical systems are rapidly developing thus contribute to the use of a dynamic video stream for detecting and initializing space objects. …”
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Accelerated development of multi-component alloys in discrete design space using Bayesian multi-objective optimisation by Osman Mamun, Markus Bause, Bhuiyan Shameem Mahmood Ebna Hai

“…This approach is particularly advantageous for deployment in massively parallel high-throughput synthesis facilities and advanced computing architectures.…”
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Computational modeling of fear and stress responses: validation using consolidated fear and stress protocols by Brunna Carolinne Rocha Silva Furriel, Brunna Carolinne Rocha Silva Furriel, Brunna Carolinne Rocha Silva Furriel, Geovanne Pereira Furriel, Mauro Cunha Xavier Pinto, Rodrigo Pinto Lemos

“…To advance the understanding of fear and stress, this study presents a biologically and behaviorally plausible computational architecture that integrates several subregions of key brain structures, such as the amygdala, hippocampus, and medial prefrontal cortex. …”
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Magnetic soliton-based LIF neurons for spiking neural networks (SNNs) in multilayer spintronic devices by Kishan K. Mishra

“…Spintronic-based technologies, particularly domain walls (DWs) and skyrmions (SKs), have shown remarkable potential for brain-inspired computing, facilitating energy-efficient data storage and advancing beyond CMOS computing architectures. Researchers have proposed various DWs- and Sks-based neuromorphic architectures for neurons and synapses. …”
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The modern architecture culture of Harbin based on memes by Jun Cai, Jianfei Dong, Yuan Zhou

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Similarity Learning and Generalization with Limited Data: A Reservoir Computing Approach by Sanjukta Krishnagopal, Yiannis Aloimonos, Michelle Girvan

“…We present two Reservoir Computing architectures, which loosely resemble neural dynamics, and show that a Reservoir Computer (RC) trained to identify relationships between image pairs drawn from a subset of training classes generalizes the learned relationships to substantially different classes unseen during training. …”
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Evaluation and comparison of methods for neuronal parameter optimization using the Neuroptimus software framework. by Máté Mohácsi, Márk Patrik Török, Sára Sáray, Luca Tar, Gábor Farkas, Szabolcs Káli

“…Neuroptimus also offers several features to support more advanced usage, including the ability to run most algorithms in parallel, which allows it to take advantage of high-performance computing architectures. We used the common interface provided by Neuroptimus to conduct a detailed comparison of more than twenty different algorithms (and implementations) on six distinct benchmarks that represent typical scenarios in neuronal parameter search. …”
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Enabling All In-Edge Deep Learning: A Literature Review by Praveen Joshi, Mohammed Hasanuzzaman, Chandra Thapa, Haithem Afli, Ted Scully

“…Firstly, this paper presents all in-edge computing architectures, including centralized, decentralized, and distributed. …”
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AI augmented edge and fog computing for Internet of Health Things (IoHT) by Deepika Rajagopal, Pradeep Kumar Thimma Subramanian

“…This study aims to examine future and existing fog and edge computing architectures and methods that have been augmented with artificial intelligence (AI) for use in healthcare applications, as well as defining the demands and challenges of incorporating fog and edge computing technology in IoHT, thereby helping healthcare professionals and technicians identify the relevant technologies required based on their need for developing IoHT frameworks for remote healthcare. …”
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Integrated Imager and 3.22 <italic>&#x03BC;</italic>s/Kernel-Latency All-Digital In-Imager Global-Parallel Binary Convolutional Neural Network Accelerator for Image Processing by Ruizhi Wang, Cheng-Hsuan Wu, Makoto Takamiya

“…Traditional CNN accelerators employing in/near-array-computing (inclusive of in/near-memory-computing and in/near-sensor-computing) architectures have struggled to meet real-time requirements due to latency bottlenecks encountered with conventional column-parallel processing for image processing. …”
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Evaluating carbon removal: Integrating technical potential with environmental, social, governance criteria, and sequestration permanence by Jan Mertens, Christian Breyer, Ronnie Belmans, Corinne Gendron, Patrice Geoffron, Carolyn Fischer, Elodie Du Fornel, Richard Lester, Kimberly A. Nicholas, Paulo Emilio V. de Miranda, Sarah Palhol, Peter Verwee, Olivier Sala, Michael Webber, Koenraad Debackere

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Enhancement of convolutional neural network for urban environment parking space classification by S. Rahman, M. Ramli, F. Arnia, R. Muharar, M. Ikhwan, S. Munzir

“…EfficientParkingNet's lightweight computing architecture can increase the speed of information on parking availability to users.CONCLUSION: EfficientParkingNet is more efficient in determining the availability of parking spaces compared to mAlexnet, but still cannot match Yolo+MobileNet. …”
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