Artificial Intelligence

On the basis of autonomous mobile tea picking robot, aiming at the shortcomings of traditional tea bud identification methods such as slow speed, low accuracy and poor adaptability, as well as people's demand for high-quality tea, the research and experiment of tea bud quality classification recognition based on YOLOv5 were carried out. Through the construction of the autonomous mobile tea picking robot visual recognition system, the data set was constructed, which mainly included tea image acquisition, enhancement and annotation.

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On the basis of autonomous mobile tea picking robot, aiming at the shortcomings of traditional tea bud identification methods such as slow speed, low accuracy and poor adaptability, as well as people's demand for high-quality tea, the research and experiment of tea bud quality classification recognition based on YOLOv5 were carried out. Through the construction of the autonomous mobile tea picking robot visual recognition system, the data set was constructed, which mainly included tea image acquisition, enhancement and annotation.

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This experiment was implemented to collect infrared images of the coal and gangue samples at the temperature of 323.15 K. Additionally, it showed that distinguishing between coal and gangue samples is feasible, although the area, thickness, and surface conditions were changed at a constant temperature during the process of capturing the infrared images. The coal and gangue were randomly collected from the same mine. The random samples had different weights, shapes, areas, thicknesses, and surface conations. 

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The B2F dataset (Biometric images of Fingerprints and Faces) has been prepared for face and fingerprint recognition, verification or classification.

The first subset (Fingerprint): This set of data presents the five finger feature vectors (of the left hand) for each person in a csv files.

The second subset (Face): This set of data presents feature vectors of face images in csv files. Feature vectors were extracted using the model (ResNet-50 + ArcFace). This set of face feature vectors represents:

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The Dravidian Spam SMS dataset has Spam and Ham messages in English, Tamil, Telugu, Kannada, and Malayalam languages. Nearly 7700 messages were collected by sending friends and other contacts a Google form. Language experts (reading and writing skills) were used to label the messages of corresponding languages carefully. The dataset also includes the Tamil verbatim messages written in English. For example, “Nee Nalama”. The Ham messages are mostly normal. Spam messages include business, annoying, and unnecessary messages an anonymous user sends.

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Visual storytelling refers to the manner of describing a set of images rather than a single image, also known as multi-image captioning. Visual Storytelling Task (VST) takes a set of images as input and aims to generate a coherent story relevant to the input images. In this dataset, we bridge the gap and present a new dataset for expressive and coherent story creation. We present the Sequential Storytelling Image Dataset (SSID), consisting of open-source video frames accompanied by story-like annotations.

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1122 Views

Seed quality has become increasingly important in seed management and operation. Seed germination testing is one of the crucial methods for seed quality assessment, as the development quality of seeds, including germination rate and growth speed of seedlings, is an important indicator of seed quality. The germination rate of soybeans is one of the criteria for identifying high-quality soybeans.

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This dataset provides valuable insights into hand gestures and their associated measurements. Hand gestures play a significant role in human communication, and understanding their patterns and characteristics can be enabled various applications, such as gesture recognition systems, sign language interpretation, and human-computer interaction. This dataset was carefully collected by a specialist who captured snapshots of individuals making different hand gestures and measured specific distances between the fingers and the palm.

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752 Views

The FMK (Finger Major Knuckle) dataset was proposed and created to support the experiments of identity verificatio of knuckles of middle and thumb fingers modalites. The images of this dataset were captured using the rear camera of an OPPO A12 smartphone. This dataset was created from 20 different subjects between the ages of 30 and 67. For each subject there are 3 images of major knuckle for the middle finger and 3 images of major knuckle for thumb finger.. The FMK dataset was proposed and constructed for testing and evaluation.

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Abstract—A novel approach is proposed in this article to boost the energy efficiency (EE) of an AoI-aware IoT network. In particular, we propose a new approach that is based a combination of simultaneous wireless information and power

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500 Views

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