Orchard-Wide Visual Perception and Autonomous Operation of Fruit Picking Robots: A Review by CHEN Mingyou, LUO Lufeng, LIU Wei, WEI Huiling, WANG Jinhai, LU Qinghua, LUO Shaoming

“…Enhanced strategies for effective fruit picking using the Eye-in-Hand system involve the development of more dexterous robotic hands and improved algorithms for precisely predicting the optimal picking point of each fruit. …”
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FUSCANet: Enhancing Skin Disease Classification Through Feature Fusion and Spatial-Channel Attention Mechanisms by Qinyang Liu, Xuan Wang, Hongjiu Liu, Xiangzhen Zang, Lei Li, Zhanlin Ji, Ivan Ganchev

“…With the widespread application of computer vision technology in dermatology, automating skin lesion classification through computer algorithms has become a crucial method for improving diagnostic efficiency and reducing the mortality rate due to malignant skin conditions. …”
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Enhanced Extraction of Blood and Tissue Time-Activity Curves in Cardiac Mouse FDG PET Imaging by Means of Constrained Nonnegative Matrix Factorization by Otman Sarrhini, Pedro D’Orléans-Juste, Jacques A. Rousseau, Jean-François Beaudoin, Roger Lecomte

“…The method is noninvasive and consists of using a constrained nonnegative matrix factorization algorithm (CNMF) applied to the matrix (A) containing the intensity values of the voxels of the left ventricle (LV) PET image. …”
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LittleFaceNet: A Small-Sized Face Recognition Method Based on RetinaFace and AdaFace by Zhengwei Ren, Xinyu Liu, Jing Xu, Yongsheng Zhang, Ming Fang

“…Traditional face recognition algorithms are typically static and rely heavily on clear images, resulting in inaccurate recognition for low-resolution, small-sized faces. …”
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Adaptive control for vehicle formation movement with multiple sensors by TANG Mingzhu, XIANG Guoliang, SHI Hongwei, GUO Shenghui

“…The adaptive motion algorithm based on predetermined motion trajectories is studied in this paper, addressing the problem of vehicle formation with multiple sensors. …”
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BucketAugment: Reinforced Domain Generalisation in Abdominal CT Segmentation by David Jozef Hresko, Peter Drotar

“…By leveraging Q-learning principles and distributed stacks of 3D augmentations, this method improves the performance of deep neural networks on medical segmentation tasks, demonstrating its potential to enhance the applicability of such models across different datasets and clinical scenarios.…”
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Explainable AI-Based Ensemble Clustering for Load Profiling and Demand Response by Elissaios Sarmas, Afroditi Fragkiadaki, Vangelis Marinakis

“…To address this shortcoming, we applied an advanced ensemble clustering method and compared its performance with traditional algorithms, namely, K-Means++, fuzzy K-Means, Hierarchical Agglomerative Clustering, Spectral Clustering, Gaussian Mixture Models (GMMs), BIRCH, and Self-Organizing Maps (SOMs), across a dataset of 5567 households for a range of cluster counts from three to nine. …”
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Power Adaptation for Optimizing Secrecy Energy Efficiency in NOMA-Enabled Underlay Cognitive Radio Networks and DNN-Based Evaluation by P. P. Hema, A. V. Babu

“…The combination of Non-orthogonal multiple access (NOMA) and cognitive radio (CR) has become a reliable solution for improving spectrum efficiency in wireless networks. …”
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Ornithological flight safety as a task of decision making in conditions of uncertainty by P. P. Hachikyan

“…An analysis of the results of the work showed that solving the problems in a field of deep uncertainty is a complex scientific task, however, the use of the new tools for scenario modeling will improve the quality of the Airline operation in providing ornithological flight safety, which will ultimately have a positive effect on reducing the risk of aviation incidents.…”
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Hand-aware graph convolution network for skeleton-based sign language recognition by Juan Song, Huixuechun Wang, Jianan Li, Jian Zheng, Zhifu Zhao, Qingshan Li

“…With the aim to further improve the performance, the joints information, bones, together with their motion information are simultaneously modeled in a multi-stream framework. …”
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Empowering Education: Leveraging Clustering and Recommendations for Enhanced Student Insights by Kheira Ouassif, Benameur Ziani, Jorge Herrera-Tapia, Chaker Abdelaziz Kerrache

“…The overarching goal was to refine adaptive learning models that cater to the diverse needs of students, improving their academic success and participation.…”
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Parallelizing Quantum Simulation With Decision Diagrams by Shaowen Li, Yusuke Kimura, Hiroyuki Sato, Masahiro Fujita

“…Quantum simulation intrinsically models the state evolution of quantum subsystems. …”
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Method of troubleshooting in the neural network environment of intellectual decision supporting systems by О.І. Тимочко, С.В. Осієвський, О.О. Тімочко, П.В. Бєляєв

“…The classification and analysis of algorithms for sampling knowledge from an artificial neural network are given. …”
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A Systematic Review of the Use of Deep Learning in Satellite Imagery for Agriculture by Brandon Victor, Aiden Nibali, Zhen He

“…The data hungry nature of deep learning models and this huge data volume seem like a perfect match. …”
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Multi-Underwater Target Interception Strategy Based on Deep Reinforcement Learning by Wenhao GAN, Yunfei PENG, Lei QIAO

“…First, a hierarchical maneuvering framework was introduced to improve the decision-making ability of AUVs through a three-layer loop structure. …”
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Small-Signal Stability Analysis and Parameters Optimization of Virtual Synchronous Generator for Low-Inertia Power System by Alaa Altawallbeh, Abdulrahman Alassi, Nader Meskin, Mohammed A. Al-Hitmi, Ahmed M. Massoud

“…We further propose a hybrid Particle Swarm Optimization (PSO) algorithm with a multi-objective cost function to optimize VSG controller gains. …”
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Advancing Agricultural Machinery Maintenance: Deep Learning-Enabled Motor Fault Diagnosis by Xusong Bai, Qian Chen, Xiangjin Song, Weihang Hong

“…This article further discusses future research directions, such as optimizing DL models for real-time processing, improving robustness under varying agricultural conditions, and developing user-friendly interfaces for farmers and technicians. …”
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MCRFS-Net: single image dehazing based on multi-scale contrastive regularization and frequency selection by Qin Qin, Lin Shui, Yanyan Zhang, Shaojing Song, Jinhua Jiang

“…Additionally, we propose a Multi-Scale Contrast Regularization (MSCR) loss function, which leverages cross-scale contrastive learning to improve feature consistency. Experimental results demonstrate that the proposed algorithm outperforms existing methods on four benchmark datasets, achieving superior detail preservation and enhanced robustness against non-uniform haze.…”
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Multi-Objective Optimization of Insulation Thickness with Respect to On-Site RES Generation in Residential Buildings by Agis M. Papadopoulos, Konstantinos Polychronakis, Elli Kyriaki, Effrosyni Giama

“…Using the DesignBuilder and EnergyPlus software, this study models a representative two-story residential building located in Athens, Greece. …”
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Abilities and limitations in counteracting urban heat islands by Michał Musiał, Anna Pomykała, Lech Lichołai

“…The ability to process vast amounts of data allows for more effective use of energy and water resources in buildings while continuously improving the algorithm. The literature review involved a comparison of current methods used to counteract urban heat islands, as well as existing and potential applications of artificial intelligence algorithms described in the Scopus and Web of Science databases. …”
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