Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…At the same time, the ReLU transfer function ensures robustness, mainly when dealing with noisy or incomplete image segments. …”
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Learning a prior on regulatory potential from eQTL data. by Su-In Lee, Aimée M Dudley, David Drubin, Pamela A Silver, Nevan J Krogan, Dana Pe'er, Daphne Koller

“…This regulatory potential is defined in terms of "regulatory features"-including the function of the gene and the conservation, type, and position of genetic polymorphisms-that are available for any organism. …”
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Transmission Lines Insulator State Detection Method Based on Deep Learning by Xu Tan, Shiying Hou, Fan Yang, Zhimin Li

“…Therefore, to achieve automation in insulator state detection, this paper proposes a method based on deep learning for insulator state detection in transmission lines. …”
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MM-HGNN: Multimodal Representation Learning Heterogeneous Graph Neural Network by Khalil Bachiri, Ali Yahyaouy, Maria Malek, Nicoleta Rogovschi

“…Abstract Multimodal learning heterogeneous graphs are very challenging because of the diverse structures and data modalities. …”
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Multi-Underwater Target Interception Strategy Based on Deep Reinforcement Learning by Wenhao GAN, Yunfei PENG, Lei QIAO

“…Therefore, this paper proposed a multi-agent deep reinforcement learning framework for AUVs to learn interception strategies in environments with complex obstacles and time-vary ocean currents, with a focus on cooperation in many-to-many game scenarios. …”
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Utilising machine learning classification models for meteorological drought monitoring and analysis by Iqra Mumtaz, Rizwan Niaz, Zamama Sajid, Abdu Qaid Alameri, Zulfiqar Ali, Khaled A. Gepreel

“…This study identifies drought events using the Standardized Precipitation Index (SPI) and applies four machine learning model Support Vector Machines (SVM), Random Forest (RF), Gradient Boosting (GB), and Logistic Regression for drought prediction. …”
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Learning From Natural Images in Few-Shot SAR Target Classification by Songhao Shi, Xiaodan Wang, Yafei Song

“…This module utilizes supervised contrastive learning to enhance intraclass compactness and interclass divergence of features. …”
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Attention with Long-Term Interval-Based Deep Sequential Learning for Recommendation by Zhao Li, Long Zhang, Chenyi Lei, Xia Chen, Jianliang Gao, Jun Gao

“…Modeling user behaviors as sequential learning provides key advantages in predicting future user actions, such as predicting the next product to purchase or the next song to listen to, for the purpose of personalized search and recommendation. …”
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Uncertainty-Aware Active Meta-Learning for Few-Shot Text Classification by Sanghyun Seo, Hiskias Dingeto, Juntae Kim

“…By quantifying the prediction uncertainty of the model for the input data, we provide a loss function and learning strategy that can adjust the influence of the input data on the model’s learning. …”
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Activity cliff-aware reinforcement learning for de novo drug design by Xiuyuan Hu, Guoqing Liu, Yang Zhao, Hao Zhang

“…In response to the limitations of current models in capturing these critical discontinuities, we propose the Activity Cliff-Aware Reinforcement Learning (ACARL) framework. ACARL leverages a novel activity cliff index to identify and amplify activity cliff compounds, uniquely incorporating them into the reinforcement learning (RL) process through a tailored contrastive loss. …”
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Autonomous and sustainable machine learning: pursuing new horizons of intelligent systems by Witold Pedrycz

“…Those manifest evidently when Machine Learning constructs have to function autonomously and any decisions being rendered entail far reaching implications. …”
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A Learned Reduced-Rank Sharpening Method for Multiresolution Satellite Imagery by Sveinn E. Armannsson, Magnus O. Ulfarsson, Jakob Sigurdsson

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Intuition-guided Reinforcement Learning for Soft Tissue Manipulation with Unknown Constraints by Xian He, Shuai Zhang, Jian Chu, Tongyu Jia, Lantao Yu, Bo Ouyang

“…A regulator factor is designed as an action within this framework to coordinate the IM approach and the SAC network. A reward function is designed to balance the exploration and exploitation of large deformations. …”
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Efficient and secure multi-party computation protocol supporting deep learning by Shancheng Zhang, Gang Qu, Zongyang Zhang, Minzhe Huang, Haochun Jin, Liqun Yang

“…Moreover, we introduce optimized protocols for two crucial deep learning operations: convolution and Softmax function computation. …”
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Grid cells, place cells, and geodesic generalization for spatial reinforcement learning. by Nicholas J Gustafson, Nathaniel D Daw

“…An important problem, though, is how complex tasks can be represented in a way that enables efficient learning. We consider this problem through the lens of spatial navigation, examining how two of the brain's location representations--hippocampal place cells and entorhinal grid cells--are adapted to serve as basis functions for approximating value over space for RL. …”
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Contrastive Speaker Representation Learning with Hard Negative Sampling for Speaker Recognition by Changhwan Go, Young Han Lee, Taewoo Kim, Nam In Park, Chanjun Chun

“…To demonstrate the effectiveness of our proposed method, we compared the performance of a deep learning model trained with a conventional loss function utilized in speaker recognition with that of a deep learning model trained using our proposed method, as measured by the equal error rate (EER), an objective performance metric. …”
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Listener Acoustic Personalization Challenge - LAP24: Head-Related Transfer Function Upsampling by Aidan O. T. Hogg, Roberto Barumerli, Rapolas Daugintis, Katarina C. Poole, Fabian Brinkmann, Lorenzo Picinali, Michele Geronazzo

“…Head-related transfer functions (HRTFs) often play a crucial role in spatial hearing, immersive audio applications for virtual reality (VR) and augmented reality (AR), and help in improving hearing assistive devices. …”
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ORGANIZATIONAL-METHODICAL BASES OF THE FUNCTIONALLY-ORIENTED TRAINING OF SPECIALISTS IN THE STRUCTURE OF REGIONAL EDUCATIONAL CLUSTER by Pavel G. Kravtsov, Valentin N. Mikhelkevich

“…It is shown that the dominant factor of the process functional-based learning is the formation and development of competencies for professional activities.…”
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An Online Paleoclimate Data Assimilation With a Deep Learning‐Based Network by Haohao Sun, Lili Lei, Zhengyu Liu, Liang Ning, Zhe‐Min Tan

“…Abstract An online paleoclimate data assimilation (PDA) that utilizes climate forecasts from a deep learning‐based network (NET) along with assimilation of proxies to reconstruct surface air temperature, is investigated here. …”
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Copper Nodule Defect Detection in Industrial Processes Using Deep Learning by Zhicong Zhang, Xiaodong Huang, Dandan Wei, Qiqi Chang, Jinping Liu, Qingxiu Jing

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