Suchergebnisse - computer learning and pattern recognition::automatic problems solving~

Automatic discovery of resource-restricted Convolutional Neural Network topologies for myoelectric pattern recognition von Olsson, Alexander E., Björkman, Anders, Antfolk, Christian

“… Convolutional Neural Networks (CNNs) have been subject to extensive attention in the pattern recognition literature due to unprecedented performance in tasks of information extraction from unstructured data …”
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Automatic assessment of cognitive and emotional states in virtual reality‐based flexibility training for four adolescents with autism von Moon, Jewoong, Ke, Fengfeng, Sokolikj, Zlatko

“… ) in interpreting, selecting and creating multimodal representations during STEM‐related design problem solving …”
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Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images von naceur, Mostefa Ben, Saouli, Rachida, Akil, Mohamed, Kachouri, Rostom

“… •A new fully automatic end-to-end deep learning model for brain tumor segmentation …”
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OPTIMOL: Automatic Online Picture Collection via Incremental Model Learning von Li, Li-Jia, Fei-Fei, Li

“… Semantic image understanding plays a vital role towards solving this problem. One important task in image understanding is object recognition, in particular, generic object categorization …”
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CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts von Carreira, J., Sminchisescu, C.

“… The object hypotheses are represented as figure-ground segmentations, and are extracted automatically, without prior knowledge of the properties of individual object classes, by solving a sequence …”
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An efficient automatic workload estimation method based on electrodermal activity using pattern classifier combinations von Ghaderyan, Peyvand, Abbasi, Ataollah

“… Automatic workload estimation has received much attention because of its application in error prevention, diagnosis, and treatment of neural system impairment …”
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Automatic music transcription for traditional woodwind instruments sopele von Skoki, Arian, Ljubic, Sandi, Lerga, Jonatan, Štajduhar, Ivan

“… •Unwanted pitch variation is mitigated using DFT and supervised machine learning.•DFT-coupled RF and CNN models achieve F1 …”
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Automatic Hint Generation for Logic Proof Tutoring Using Historical Data von Barnes, Tiffany, Stamper, John

“… In building intelligent tutoring systems, it is critical to be able to understand and diagnose student responses in interactive problem solving …”
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Associating Facial Expressions and Upper-Body Gestures with Learning Tasks for Enhancing Intelligent Tutoring Systems von Behera, Ardhendu, Matthew, Peter, Keidel, Alexander, Vangorp, Peter, Fang, Hui, Canning, Susan

“… In this paper, we explore the automatic detection of learner’s nonverbal behaviors involving hand-over-face gestures, head and eye movements and emotions via facial expressions during learning …”
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Active Learning for Solving the Incomplete Data Problem in Facial Age Classification by the Furthest Nearest-Neighbor Criterion von Jian-Gang Wang, Sung, E, Wei-Yun Yau

“… One of the difficulties in applying learning techniques to the age classification problem is the large amount of labeled training data required …”
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A Case-Based Recommendation Approach for Market Basket Data von Gatzioura, Anna, Sanchez-Marre, Miquel

“… The scope of the presented approach is to generate meaningful recommendations based on items' co-occurring patterns and to provide more insight into customers' buying habits …”
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A unified perspective and new results on RHT computing, mixture based learning, and multi-learner based problem solving von Xu, Lei

“… learning, multi-sets mixture based object detection and motion estimation, and multi-agent coordinated problem solving …”
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A Computational Learning Theory of Active Object Recognition Under Uncertainty von Andreopoulos, Alexander, Tsotsos, John K.

“… We prove that under certain conditions, the corresponding classes of object localization and recognition problems are efficiently …”
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Classifier and Exemplar Synthesis for Zero-Shot Learning von Changpinyo, Soravit, Chao, Wei-Lun, Gong, Boqing, Sha, Fei

“… Zero-shot learning (ZSL) enables solving a task without the need to see its examples …”
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A twin-hyperspheres support vector machine with automatic variable weights for data classification von Peng, Xinjun, Shen, Jindong

“… By solving a single optimization problem, this classifier not only finds a pair of hyperspheres for classification, but also automatically constructs a weight vector for each class in order …”
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Leveraging two-level deep learning classifiers for 2D shape recognition to automatically solve geometry math word problems von Boob, Archana, Radke, Mansi

“… This advantage is particularly salient in the era of online and hybrid tutoring, where automatic QA systems have become vital in addressing complex mathematical problems …”
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Locality Preserving Property Constrained Contrastive Learning for Object Classification in SAR Imagery von Wang, Jing, Tian, Sirui, Feng, Xiaolin, Zhang, Bo, Wu, Fan, Zhang, Hong, Wang, Chao

“… ) automatic target recognition (ATR) with limited labeled data. The developing contrastive self-supervised learning (CSL …”
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Research on Communication Signal Modulation Recognition Based on a CCLDNN von He, Zijin, Zeng, Xiaodong

“… In this paper, a new automatic modulation recognition (AMR) method named CCLDNN (complex-valued convolution long short-term memory deep neural network) is proposed …”
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Solving multi-class problems by data-driven topology-preserving output codes von Zhang, Junying, Zhao, Xiaoxue, Du, Lan

“… Aiming at decomposing a complex multi-class problem into fewer and simpler sub-problems to gain an overall classifier of low complexity, we propose a universal data-driven topology-preserving output code (TPOC …”
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Joint analysis of radiological reports and CT images for automatic validation of pathological brain conditions von Agafonova, Y.D., Gaidel, A.V., Zelter, P.M., Kapishnikov, A.V., Kuznetsov, A.V., Surovtsev, E.N., Nikonorov, A.V.

“… Two methods for solving the problem are proposed: a method based on the ruCLIP multimodal model, and a method based on the joint use of two separate classifiers …”
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