To address the problem of online automatic inspection of drug liquid bottles in production line, an implantable visual inspection system is designed and the ensemble learning algorithm for detection is proposed based on multi-features fusion. A tunnel structure is designed for visual inspection system, which allows the bottles inspection to be automated without changing original processes and devices. A high precision method is proposed for vision detection of drug liquid bottles.

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The dataset contains 236 X-ray images, all of which include the top of the head to the middle of the thigh. The included patients are 18-80 years old, and treated to the department of orthopedics due to low back pain or spinal deformity. The original size of the X-ray images is around 3000×7000px.

 

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DIDA is a new image-based historical handwritten digit dataset and collected from the Swedish historical handwritten document images between the year 1800 and 1940. It is the largest historical handwritten digit dataset which is introduced to the Optical Character Recognition (OCR) community to help the researchers to test their optical handwritten character recognition methods. To generate DIDA, 250,000 single digits and 200,000 multi-digits are cropped from 75,000 different document images. 

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Dataset including over 40,000 generated images of malicious binaries for malware classification in machine learning as outlined in NARAD - A Novel Auto-learn Real-time Fuzzy Machine Learning Anomaly Detection and Classification System.

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The dataset consists all the Telugu characters that contains Vowels, Consonants and combine characters such as Othulu (Consonant-Consonant) and Guninthamulu (Consonant-Volwels). The main objective of this dataset to recognize handwritten Telugu characters, from that convert handwritten document into editable electronic copy.

Instructions: 

All the images are in the same size and all images are scanned by scanner and segmented manually and all images are jpeg images.

 Acknowledgement:

 The work is carried out under Collaborative Research Project Sponsored by JNTU Hyderabad, India. The project file no. JNTUH/TEQIP-III/CRS/2019/CSE/12 and Titled as "Deep Learning Aided-OCR for Handwritten Telugu Character".

 

 

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The first bit of light is the gesture of being, on a massive screen of the black panorama. A small point of existence, a gesture of being. The universal appeal of gesture is far beyond the barriers of languages and planets. These are the microtransactions of symbols and patterns which have traces of the common ancestors of many civilizations.Gesture recognition is important to make communication between the computer system and humans, in the present era many studies are going on regarding the gesture recognition systems.

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A set of chest CT data sets from multi-centre hospitals included five categories

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Mosquito bites result in the deaths of more than 1 million people every year.   Certain species of mosquitos like Aedes are the main vector of arboviruses that cause Dengue, Malaria and Yellow fever. Image based mosquito species classification can be helpful to implement strategies to prevent the spread of mosquito borne disease. Automated mosquito species classification can aid in laborious and time consuming task of entomologists besides enhancing accuracy.

Instructions: 

The dataset consists of images of two species of mosquitoes namely Aedes and Culex .  

There are 810 images of Aedes and 594 images of Culex class.

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1003 Views

Recognition and classification of currency is one of the important task. It is a very crucial task for visually impaired people. It helps them while doing day to day financial transactions with shopkeepers while traveling, exchanging money at banks, hospitals, etc. The main objectives to create this dataset were:

        1)      Create a dataset of old and new Indian currency.

        2)      Create a dataset of Thai Currency.

        3)      Dataset consists of high-quality images.

Instructions: 

The dataset consists of 10 classes namely 10 New, 10 Old, 20, 50 New, 50 Old, 100 New, 100 Old, 200, 500, 2000 of Indian banknotes and 5 classes namely 20, 50, 100, 500, and 2000 for Thai bank notes.

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INDIA is the second-largest fruit and vegetable exporter in the world after China. It ranked first in the production of Bananas, Papayas, and Mangoes. Public datasets of fruits are available but they are limited to general fruit classes and failed to classify the fruits according to the fruit quality. To overcome this problem, we have created a dataset named FruitsGB (Fruits Good/Bad) dataset.

Instructions: 

The data set contains 12 classes of fruits namely Bad Apple, Good Apple, Bad Banana, Good Banana, Bad Guava, Good Guava, Bad Lime, Good Lime, Bad Orange, Good Orange, Bad Pomegranate, and Good Pomegranate.

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2522 Views