Single image rain streak removal is an extremely challenging problem due to the presence of non-uniform rain densities in images. We present a novel densityaware multi-stream densely connected convolutional neural network-based algorithm, called DID-MDN, for joint rain density estimation and de-raining. The proposed method enables the network itself to automatically determine the rain-density i...

The road sign recognition (RSR) system is used to complete two tasks: localizing the traffic in an image and then classifying it according features. Some of applications such are incorporated into Advanced Driver Assistance System (ADAS) autonomous vehicles. However, accuracy model decreases when changes lighting or weather occurs, lack training samples taken rainy condition causes be sub-optim...

Maize (Zea mays) is one of the most important cereal crops grown principally during raining season in Ethiopia which commonly used for both human consumption and poultry feed. Green house experiment on effect watering frequency germination early growth maize was carried out at Ambo Agricultural Research Center using a hybrid variety (Jibat) from December 1 to January20th, 2018/19. The study con...

T raining for functional fitness has become an increasingly popular approach for personal trainers and strength coaches alike. According to Okada et al. (15), functional movement can be defined as the ability to produce and maintain a balance between mobility and stability along a kinetic chain while carrying out fundamental patterns with accuracy and efficiency. Given this definition, the prim...

The Monty Hall problem (or three-door problem) is a famous example of a "cognitive illusion," often used to demonstrate people's resistance and deficiency in dealing with uncertainty. The authors formulated the problem using manipulations in 4 cognitive aspects, namely, natural frequencies, mental models, perspective change, and the less-is-more effect. These manipulations combined led to a sig...

We stud y th e amount of ti me needed to learn a fixed t raining se t in the "back-pro pagation" proced ure for learning in multi-layer neural network models. The task chosen was 32-bit parity, a highorder funct ion for wh ich memorization of specific inpu t-output pairs is necessary. For small t raining sets , the learning time is consistent with a ~-power law depen dence on the number of patt...