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Convolutional
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50 documents available in our comprehensive collection of Convolutional resources. Find practical guides, tutorials, and documentation to enhance your knowledge.
Convolutional Text Encoding (paper3.pdf)
899 KBEN 10 pages
Researchers propose a lightweight convolutional architecture for creating fixed-size vector embeddings of sentences, useful for building NLP systems, including
Deformable CNNs (1703.06211.pdf)
6.63 MBEN 12 pages
Deformable convolutional networks introduce two new modules, deformable convolution and deformable RoI pooling, to enhance transformation modeling capability
Depth Estimation (2003.06637.pdf)
10.4 MBEN 5 pages
A novel learning-based framework for fast depth estimation from stereo images is proposed, utilizing dilated convolution, densely connected convolutional
Attentive Convolution (Q18-1047.pdf)
1.03 MBEN 16 pages
Attentive convolution networks (ATTCONV) are proposed to equip CNNs with RNN-style attention mechanisms, extending the context scope of convolution operations...
convolutional deep learning networks (1511.06530.pdf)
1022 KBEN 16 pages
Researchers from Samsung Electronics and Seoul National University proposed a simple and effective scheme to compress deep convolutional neural networks (CNNs)
RubiksNet: Learnable 3D Shift for Efficient Video Action Recognition (eccv20.pdf)
3.08 MBEN 17 pages
RubiksNet is an efficient architecture for video action recognition that replaces temporal convolutions with a learnable 3D spatiotemporal shift operation, reducing computational cost while maintaining accuracy. This approach avoids the bottlenecks of standard 3D convolution...
On the Integration of Self-Attention and Convolution. (2111.14556.pdf)
1.44 MBEN 16 pages
Researchers from Tsinghua University and Huawei Technologies propose a new model, ACmix, that integrates self-attention and convolution techniques for...
William Gilpin; Cellular automata as convolutional neural networks (1809.02942.pdf)
4.51 MBEN 12 pages
Deep learning techniques have demonstrated success in predicting complex dynamical systems, motivating questions about how neural networks encode and represent...
(Song_Box-Driven_Class-Wise_Region_Masking_and_Filling_Rate_Guided_Loss_for_CVPR_2019_paper.pdf)
1.36 MBEN 10 pages
Semantic segmentation has made significant progress with deep Fully Convolutional Networks (FCN), but its performance relies heavily on expensive and
Deep Learning Optimization (03_775-788_00920_Bpast.No_.66-6_31.12.18_K2.pdf)
5.43 MBEN 13 pages
The landscape of empirical risk of overparametrized deep convolutional neural networks (DCNNs) is characterized by a large number of global minimizers with
Neonatal Seizure Detection (CNN_seizure.pdf)
1.39 MBEN 20 pages
Researchers used deep convolutional neural networks (CNNs) and random forest to automatically optimize feature selection and classification for neonatal
Turbo Code Reliability (c-37.pdf)
508 KBEN 10 pages
Turbo codes are parallel concatenation of two recursive systematic convolutional codes with an interleaver, achieving performances within 2 dB of channel
Foreign Object Detection (118.pdf)
121 KBEN 1 page
An efficient foreign object intrusion detection method for ballast tracks is proposed using a deep segmentation convolutional neural network, enabling quick
Learning Deep Features for Discriminative Localization (1512.04150.pdf)
2.49 MBEN 10 pages
Researchers revisit global average pooling in convolutional neural networks (CNNs), finding it enables remarkable localization ability despite being trained on
pdf (30-CR.pdf)
498 KBEN 14 pages
The team experimented with two classification techniques: convolutional neural networks (CNN) and Fisher vectors-based discriminant models
https://arxiv.org/pdf/2204.10408.pdf (2204.10408.pdf)
1.11 MBEN 7 pages
ICDBigBird is a contextual embedding model for ICD code classification, combining a Graph Convolutional Network (GCN) with a BigBird contextual model to
Gear Pitting Fault Diagnosis using Acoustic Emission (pdf-158286-84583)
1.39 MBEN 8 pages
Gear pitting fault detection crucial for industrial equipment reliability. Traditional methods use vibration signals and machine learning for diagnosis.
PDF (2008.07989.pdf)
2.15 MBEN 13 pages
Researchers propose a one-class classification approach using convolutional autoencoders for fingerprint presentation attack detection, trained only on bona
Liver Lesion Segmentation (1707.07734.pdf)
514 KBEN 4 pages
Researchers propose a joint segmentation model for liver and liver lesions in CT volumes, using two fully convolutional networks trained end-to-end, achieving
CRF-RNN Model (Zheng_Conditional_Random_Fields_ICCV_2015_paper.pdf)
1010 KBEN 9 pages
Conditional Random Fields are formulated as Recurrent Neural Networks to combine the strengths of Convolutional Neural Networks and CRFs for pixel-level
Article (PDF) (pdf-156091-86096)
1.65 MBEN 18 pages
Researchers presented a methodology for automated analysis of chip shapes using image processing and a convolutional neural network (CNN), enabling
Green Version (isprs-archives-XLII-3-W8-1-2019.pdf)
967 KBEN 7 pages
This study proposes a deep learning approach for detecting chestnut clusters using Convolutional Neural Networks (CNNs), specifically the Xception
PlaneMatch (1803.08407.pdf)
7.68 MBEN 31 pages
Researchers introduce PlaneMatch, a deep convolutional neural network for detecting coplanar surfaces in SLAM reconstruction, which takes RGB, depth, and
Download PDF (12922-52-16439-1-2-20201228.pdf)
621 KBEN 7 pages
A deep convolutional neural network (CNN) is used to select abstract actions in real-time strategy games, and the remaining computation time is utilized for
Fourier CNN Forecasting (ds2019.pdf)
283 KBEN 10 pages
Researchers propose a time series forecasting framework using Convolutional Neural Networks (CNNs) that integrates required preprocessing steps and makes no
Full paper (1706.04313.pdf)
9.43 MBEN 10 pages
Convolutional neural networks (CNNs) have shown great success in computer vision, but typically do not exhibit compositionality, where the representation of
PDF document (v9i2p6.pdf)
239 KBEN 23 pages
The Australian Journal of Mathematical Analysis and Applications discusses linear Volterra integral equations with convolution kernels.
Download Paper (Badura.pdf)
17.65 MBEN 23 pages
Convolutional neural networks (CNNs) are used to infer the attitude status of resident space objects (RSOs) from simulated light curve measurements
Facial Engagement Detection (2021043021.pdf)
688 KBEN 12 pages
Researchers propose a shallow residual convolutional neural network to detect engagement through facial emotional recognition, achieving 91
(1708.04943.pdf)
1.92 MBEN 12 pages
Researchers propose a Stacked Deconvolutional Network (SDN) for semantic image segmentation, addressing the issue of spatial resolution loss in Fully
Edge Inference Optimization (2206.07741.pdf)
4.89 MBEN 15 pages
This paper proposes a new quantization approach for mixed precision convolutional neural networks (CNNs) targeting edge-computing, achieving a new Pareto
IJAEM Publication (648130.pdf)
485 KBEN 1 page
Ashili Alex, Ansiya, Ashna S, Athulya S Nair, Shahul Hameed A published "Hand Sign Identification System Using Convolutional Neural Network" in the
End2End Driving (1604.07316.pdf)
1.23 MBEN 9 pages
NVIDIA researchers trained a convolutional neural network (CNN) to map raw pixels from a single front-facing camera to steering commands, enabling a car to
2D Pose Estimation (McNally_William.pdf)
15.15 MBEN 126 pages
William McNally's PhD thesis presents two novel convolutional neural networks for 2D human pose estimation, one for single-stage and one for two-stage
Download (Factorized_Higher-Order_CNNs_for_Spatio-Temporal_Emotion_Estimation.pdf)
802 KBEN 10 pages
Researchers propose a tensor factorization framework for efficient multidimensional convolutions of higher-order, unifying approaches to compress networks and...
Sign Phonology Modeling (ES2023-83.pdf)
1.62 MBEN 6 pages
Researchers explored strategies for modeling sign language phonology, focusing on recognizing 16 phoneme types in ASL-LEX 2.0 using graph convolution networks.
Data Fusion of Post-disaster VHR Aerial Imagery and LiDAR Data for Roof Classification using Convolutional Neural Networks (2307.16177.pdf)
4.69 MBEN 8 pages
Researchers leveraged deep learning techniques to classify roof characteristics from very high-resolution orthophotos and airborne LiDAR data obtained in...
Download PDF (Brain-morph.pdf)
3.14 MBEN 15 pages
Researchers studied the growth and form of cortical convolutions in the human brain, using magnetic resonance images to build a 3D-printed layered gel mimic of...
PDF File (cvpr-2004.pdf)
752 KBEN 8 pages
Yann LeCun, Fu Jie Huang, and Léon Bottou assessed learning methods for generic object recognition with invariance to pose and lighting.
Efficient supervised sparse analysis and synthesis operators (SprLitBenBroSapNIPS13.pdf)
627 KBEN 9 pages
It formulates a unified approach that can be optimized for specific tasks, such as reconstruction or classification, using a bilevel optimization problem.
Fracking Sarcasm (W16-0425.pdf)
304 KBEN 9 pages
Researchers propose a neural network semantic model for sarcasm detection, outperforming state-of-the-art text-based methods with an F-score of 0.92, using a...
http://ceur-ws.org/Vol-2266/T1-3.pdf (T1-3.pdf)
299 KBEN 3 pages
DAIICT-Hildesheim participated in the IRMiDis 2018 track with three runs to distinguish between fact-checkable and non-fact-checkable tweets.
electronic edition @ ceur-ws.org (open access) (paper2.pdf)
1.09 MBEN 10 pages
Researchers propose an attention-based deep learning model for predicting rapid intensification (RI) of tropical cyclones from satellite images, aiming to...
LREC Sign Language (2020.lrec-1.740.pdf)
6.55 MBEN 9 pages
Researchers propose a new version of the Dicta-Sign corpus for French Sign Language, including 11 hours of video recordings with 35,000 manual units, and...
Sentinel-2 Imagery for Fine-Grained Road Map Extraction Using Deep Learning Techniques (isprs-annals-V-3-2021-9-2021.pdf)
3.15 MBEN 6 pages
This study explores extracting detailed road maps using Sentinel-2 satellite imagery with deep learning techniques, specifically convolutional neural networks (CNNs)
Deprojection Recovery (1909.00475.pdf)
2.07 MBEN 10 pages
We introduce visual deprojection, recovering an image or video collapsed along a dimension, and propose a probabilistic model and variational inference...
EventStatus Corpus (D16-1005.pdf)
151 KBEN 11 pages
Researchers introduce the EventStatus corpus, a dataset of 4500 English and Spanish news articles about civil unrest events labeled as PAST, ON-GOING, or...
paper (GSchwartz_CPCV13.pdf)
4.82 MBEN 8 pages
Researchers propose "visual material traits" to recognize material properties at the pixel level, without relying on object-specific information.
Action Recognition (journal.pcbi_.1005859.pdf)
9.24 MBEN 20 pages
Researchers tested the hypothesis that invariant action discrimination drives neural representations of action sequences, finding that spatiotemporal...
Hierarchical Generative Model for Mid-Level Auditory Representations of Natural Sounds (Wiktor_COSYNE_2015_hierarchy_final.pdf)
2.52 MBEN 2 pages
Researchers from MIT's Department of Brain and Cognitive Sciences explore how neurons process natural sounds, focusing on the hierarchical coding strategies that enable auditory perception by combining low-level acoustic patterns into complex structures. Their work aims to...
Popular Keywords
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