Automated Meter Reading Detection Using Inception with Single Shot Multi-Box Detector
نویسندگان
چکیده
منابع مشابه
Weaving Multi-scale Context for Single Shot Detector
Aggregating context information from multiple scales has been proved to be effective for improving accuracy of Single Shot Detectors (SSDs) on object detection. However, existing multi-scale context fusion techniques are computationally expensive, which unfavorably diminishes the advantageous speed of SSD. In this work, we propose a novel network topology, called WeaveNet, that can efficiently ...
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SSD [18] is one of the state-of-the-art object detection algorithms, and it combines high detection accuracy with real-time speed. However, it is widely recognized that SSD is less accurate in detecting small objects compared to large objects, because it ignores the context from outside the proposal boxes. In this paper, we present CSSD– a shorthand for context-aware single-shot multibox object...
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Automated Meter reading systems are a invaluable technological advancement that can lead to a better standard of living, owing to the fact that metering has become a part and parcel of our mundane lives. It solves many issues of the traditional meter reading system like need for human resources, efficiency, accuracy, delayed work, unavailability of customer during metering visit by employee, et...
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The main contribution of this paper is an approach for introducing additional context into state-of-the-art general object detection. To achieve this we first combine a state-ofthe-art classifier (Residual-101 [14]) with a fast detection framework (SSD [18]). We then augment SSD+Residual101 with deconvolution layers to introduce additional largescale context in object detection and improve accu...
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ژورنال
عنوان ژورنال: Intelligent Automation & Soft Computing
سال: 2021
ISSN: 1079-8587
DOI: 10.32604/iasc.2021.014250