Search Results - "Neurocomputing (Amsterdam)"

A comprehensive survey on support vector machine classification: Applications, challenges and trends by Cervantes, Jair, Garcia-Lamont, Farid, Rodríguez-Mazahua, Lisbeth, Lopez, Asdrubal

“…In recent years, an enormous amount of research has been carried out on support vector machines (SVMs) and their application in several fields of science. SVMs…”
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Activation functions in deep learning: A comprehensive survey and benchmark by Dubey, Shiv Ram, Singh, Satish Kumar, Chaudhuri, Bidyut Baran

“…Neural networks have shown tremendous growth in recent years to solve numerous problems. Various types of neural networks have been introduced to deal with…”
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Recent advances in deep learning for object detection by Wu, Xiongwei, Sahoo, Doyen, Hoi, Steven C.H.

“…Object detection is a fundamental visual recognition problem in computer vision and has been widely studied in the past decades. Visual object detection aims…”
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RIME: A physics-based optimization by Su, Hang, Zhao, Dong, Heidari, Ali Asghar, Liu, Lei, Zhang, Xiaoqin, Mafarja, Majdi, Chen, Huiling

“…•A novel global optimization algorithm, rime optimization algorithm (RIME), is proposed.•RIME simulates the growth and crossover behavior of the rime-particle…”
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Deep visual domain adaptation: A survey by Wang, Mei, Deng, Weihong

“…Deep domain adaptation has emerged as a new learning technique to address the lack of massive amounts of labeled data. Compared to conventional methods, which…”
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SRDiff: Single image super-resolution with diffusion probabilistic models by Li, Haoying, Yang, Yifan, Chang, Meng, Chen, Shiqi, Feng, Huajun, Xu, Zhihai, Li, Qi, Chen, Yueting

“…Single image super-resolution (SISR) aims to reconstruct high-resolution (HR) images from given low-resolution (LR) images. It is an ill-posed problem because…”
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Online continual learning in image classification: An empirical survey by Mai, Zheda, Li, Ruiwen, Jeong, Jihwan, Quispe, David, Kim, Hyunwoo, Sanner, Scott

“…Online continual learning for image classification studies the problem of learning to classify images from an online stream of data and tasks, where tasks may…”
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Deep face recognition: A survey by Wang, Mei, Deng, Weihong

“…Deep learning applies multiple processing layers to learn representations of data with multiple levels of feature extraction. This emerging technique has…”
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Deep learning in video multi-object tracking: A survey by Ciaparrone, Gioele, Luque Sánchez, Francisco, Tabik, Siham, Troiano, Luigi, Tagliaferri, Roberto, Herrera, Francisco

“…The problem of Multiple Object Tracking (MOT) consists in following the trajectory of different objects in a sequence, usually a video. In recent years, with…”
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Federated learning on non-IID data: A survey by Zhu, Hangyu, Xu, Jinjin, Liu, Shiqing, Jin, Yaochu

“…Federated learning is an emerging distributed machine learning framework for privacy preservation. However, models trained in federated learning usually have…”
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A survey of deep neural network architectures and their applications by Liu, Weibo, Wang, Zidong, Liu, Xiaohui, Zeng, Nianyin, Liu, Yurong, Alsaadi, Fuad E.

“…Since the proposal of a fast learning algorithm for deep belief networks in 2006, the deep learning techniques have drawn ever-increasing research interests…”
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Bidirectional LSTM with attention mechanism and convolutional layer for text classification by Liu, Gang, Guo, Jiabao

“…•For the convolutional layer, the convolution window size and the stride size affect the classification performance.•BiLSTM and attention mechanism have…”
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Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks by Wang, Guotai, Li, Wenqi, Aertsen, Michael, Deprest, Jan, Ourselin, Sébastien, Vercauteren, Tom

“…•Different types of uncertainties for deep-learning based medical image segmentation were analysed.•We propose a general aleatoric uncertainty estimation…”
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A review of clustering techniques and developments by Saxena, Amit, Prasad, Mukesh, Gupta, Akshansh, Bharill, Neha, Patel, Om Prakash, Tiwari, Aruna, Er, Meng Joo, Ding, Weiping, Lin, Chin-Teng

“…This paper presents a comprehensive study on clustering: exiting methods and developments made at various times. Clustering is defined as an unsupervised…”
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A comprehensive review on convolutional neural network in machine fault diagnosis by Jiao, Jinyang, Zhao, Ming, Lin, Jing, Liang, Kaixuan

“…•The description of several popular datasets for machine fault diagnosis are presented.•This work introduces the basic theories on convolutional network and…”
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A survey on Deep Learning based bearing fault diagnosis by Hoang, Duy-Tang, Kang, Hee-Jun

“…Nowadays, Deep Learning is the most attractive research trend in the area of Machine Learning. With the ability of learning features from raw data by deep…”
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Hybrid Whale Optimization Algorithm with simulated annealing for feature selection by Mafarja, Majdi M., Mirjalili, Seyedali

“…•Four hybrid feature selection methods for classification task are proposed.•Our hybrid method combines Whale Optimization Algorithm with simulated…”
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An introduction to Deep Learning in Natural Language Processing: Models, techniques, and tools by Lauriola, Ivano, Lavelli, Alberto, Aiolli, Fabio

“…Natural Language Processing (NLP) is a branch of artificial intelligence that involves the design and implementation of systems and algorithms able to interact…”
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Time series forecasting of petroleum production using deep LSTM recurrent networks by Sagheer, Alaa, Kotb, Mostafa

“…Time series forecasting (TSF) is the task of predicting future values of a given sequence using historical data. Recently, this task has attracted the…”
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RoFormer: Enhanced transformer with Rotary Position Embedding by Su, Jianlin, Ahmed, Murtadha, Lu, Yu, Pan, Shengfeng, Bo, Wen, Liu, Yunfeng

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