Frame (networking) ≈ Frame (networking)
View article: Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning Open
Very deep convolutional networks have been central to the largest advances in image recognition performance in recent years. One example is the Inception architecture that has been shown to achieve very good performance at relatively low c…
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You Only Look Once: Unified, Real-Time Object Detection Open
We present YOLO, a new approach to object detection. Prior work on object detection repurposes classifiers to perform detection. Instead, we frame object detection as a regression problem to spatially separated bounding boxes and associate…
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Implementation of Total Productive Maintenance on Frame Welding Machine Maintenance Using the Overall Equipment Effectiveness (OEE) Method at PT Electronics Components Indonesia Open
PT. Electronics Components Indonesia manufactures capacitors and focuses on enhancing productivity and operational efficiency of the frame welding machines through effective maintenance. This study employs a quantitative method to analyze …
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ITRF2014: A new release of the International Terrestrial Reference Frame modeling nonlinear station motions Open
For the first time in the International Terrestrial Reference Frame (ITRF) history, the ITRF2014 is generated with an enhanced modeling of nonlinear station motions, including seasonal (annual and semiannual) signals of station positions a…
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A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction Open
Inspired by recent advances in deep learning, we propose a framework for reconstructing dynamic sequences of 2-D cardiac magnetic resonance (MR) images from undersampled data using a deep cascade of convolutional neural networks (CNNs) to …
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ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verification Open
Current speaker verification techniques rely on a neural network to extract\nspeaker representations. The successful x-vector architecture is a Time Delay\nNeural Network (TDNN) that applies statistics pooling to project\nvariable-length u…
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Is Space-Time Attention All You Need for Video Understanding? Open
We present a convolution-free approach to video classification built exclusively on self-attention over space and time. Our method, named "TimeSformer," adapts the standard Transformer architecture to video by enabling spatiotemporal featu…
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Siamese Instance Search for Tracking Open
In this paper we present a tracker, which is radically different from state-of-the-art trackers: we apply no model updating, no occlusion detection, no combination of trackers, no geometric matching, and still deliver state-of-the-art trac…
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YouTube-8M: A Large-Scale Video Classification Benchmark Open
Many recent advancements in Computer Vision are attributed to large datasets. Open-source software packages for Machine Learning and inexpensive commodity hardware have reduced the barrier of entry for exploring novel approaches at scale. …
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Generating Videos with Scene Dynamics Open
We capitalize on large amounts of unlabeled video in order to learn a model of scene dynamics for both video recognition tasks (e.g. action classification) and video generation tasks (e.g. future prediction). We propose a generative advers…
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Word2Vec Open
My last column ended with some comments about Kuhn and word2vec. Word2vec has racked up plenty of citations because it satisifies both of Kuhn’s conditions for emerging trends: (1) a few initial (promising, if not convincing) successes tha…
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BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling. Open
Datasets drive vision progress and autonomous driving is a critical vision application, yet existing driving datasets are impoverished in terms of visual content. Driving imagery is becoming plentiful, but annotation is slow and expensive,…
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DeMoN: Depth and Motion Network for Learning Monocular Stereo Open
In this paper we formulate structure from motion as a learning problem. We\ntrain a convolutional network end-to-end to compute depth and camera motion\nfrom successive, unconstrained image pairs. The architecture is composed of\nmultiple …
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ChatGPT outperforms crowd workers for text-annotation tasks Open
Many NLP applications require manual text annotations for a variety of tasks, notably to train classifiers or evaluate the performance of unsupervised models. Depending on the size and degree of complexity, the tasks may be conducted by cr…
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Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN Features Open
Recurrent neural network (RNN) and long short-term memory (LSTM) have achieved great success in processing sequential multimedia data and yielded the state-of-the-art results in speech recognition, digital signal processing, video processi…
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Drug discovery and development: Role of basic biological research Open
This article provides a brief overview of the processes of drug discovery and development. Our aim is to help scientists whose research may be relevant to drug discovery and/or development to frame their research report in a way that appro…
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The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6 Open
The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance c…
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A Novel Performance Evaluation Methodology for Single-Target Trackers Open
This paper addresses the problem of single-target tracker performance evaluation. We consider the performance measures, the dataset and the evaluation system to be the most important components of tracker evaluation and propose requirement…
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Tune: A Research Platform for Distributed Model Selection and Training Open
Modern machine learning algorithms are increasingly computationally demanding, requiring specialized hardware and distributed computation to achieve high performance in a reasonable time frame. Many hyperparameter search algorithms have be…
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<i>Gaia</i>Data Release 1 Open
Gaia Data Release 1 (Gaia DR1) contains astrometric results for more than 1 billion stars brighter than magnitude 20.7 based on observations collected by the Gaia satellite during the first 14 months of its operational phase. We give a bri…
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Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound Open
FIGURES 75–82. K. strigicollis (Spinola) 75. Pygophore, lateral view; 76. Subgenital plate, ventral view; 77. Apex of aedeagus, caudal view; 78. Aedeagus, lateral view; 79. Pygofer ventral process, ventral view; 80. Apophysis of style, lat…
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Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation Open
Skeleton-based human action recognition has recently drawn increasing attentions with the availability of large-scale skeleton datasets. The most crucial factors for this task lie in two aspects: the intra-frame representation for joint co…
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Variable selection with stepwise and best subset approaches Open
While purposeful selection is performed partly by software and partly by hand, the stepwise and best subset approaches are automatically performed by software. Two R functions stepAIC() and bestglm() are well designed for stepwise and best…
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BEVDepth: Acquisition of Reliable Depth for Multi-View 3D Object Detection Open
In this research, we propose a new 3D object detector with a trustworthy depth estimation, dubbed BEVDepth, for camera-based Bird's-Eye-View~(BEV) 3D object detection. Our work is based on a key observation -- depth estimation in recent ap…
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Automated Indent Scanning: Artificial intelligence assisted scanning of large regular and irregular nanoindentation arrays in scanning electron microscopes Open
Recording larger arrays of indents is a tedious and time intensive task. This project aims to automate this process through the use of the Python API provided by the Tescan microscope (SharkSEM), simple automation scripts, and the use of o…
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Multi-particle cryo-EM refinement with M visualizes ribosome-antibiotic complex at 3.5 Å in cells Open
Cryo-electron microscopy (cryo-EM) enables macromolecular structure determination in vitro and inside cells. In addition to aligning individual particles, accurate registration of sample motion and three-dimensional deformation during expo…
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Attentive Statistics Pooling for Deep Speaker Embedding Open
This paper proposes attentive statistics pooling for deep speaker embedding\nin text-independent speaker verification. In conventional speaker embedding,\nframe-level features are averaged over all the frames of a single utterance to\nform…
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Saliency-Aware Video Object Segmentation Open
Video saliency, aiming for estimation of a single dominant object in a sequence, offers strong object-level cues for unsupervised video object segmentation. In this paper, we present a geodesic distance based technique that provides reliab…
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An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data Open
Human action recognition is an important task in computer vision. Extracting discriminative spatial and temporal features to model the spatial and temporal evolutions of different actions plays a key role in accomplishing this task. In thi…
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The i-frame and the s-frame: How focusing on individual-level solutions has led behavioral public policy astray Open
An influential line of thinking in behavioral science, to which the two authors have long subscribed, is that many of society's most pressing problems can be addressed cheaply and effectively at the level of the individual, without modifyi…