• Mrunal Bhilare
• Taran Bhavsar
• Abhishek Ogale
• Harshal Hulke
• SanjeevKumar Angadi

Presently research has explored embedding supplementary information from various biometric ways like fingerprints, face, iris, palm, voice, gender, age, beard, moustache, scars, height, hair, skin color, specs, weight, facial marks, tattoos etc. All this information contributes further and further during identification. The major change that comes across face recognition is to find the age & gender of the person. This paper contributes a significant check of colorful face recognition ways for predicting age and gender. This paper also provides unborn directions for further exploration. Age and gender, two of the crucial facial attributes, play a veritably foundational part in social relations, making age and gender estimation from a single face image an important task in intelligent operations. This design is grounded upon deep learning. A Convolutional Neural Network is a deep neural network (DNN) extensively used for the purposes of image recognition and processing. A fast and effective gender and age estimation system grounded on facial images is developed. There are numerous styles that have been proposed in the literature for the age estimation and gender bracket. still, all of them have still disadvantage similar to not complete reflection about-face structure, and face texture. In this paper, we parade that by learning representations through the use of significant CNN, a huge addition in prosecution can be acquired on these errands. We have tested our model on the recent UTKFace dataset for age and gender estimation and demonstrated it to radically outflank current state-of-the-art styles.

ConvNet, AGPC (Age and gender prediction using ConvNet), UTKFace, DNN (Deep Neural Network)

"Age and Gender Prediction using ConvNet ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.h763-h766, June-2022, Available :http://www.jetir.org/papers/JETIR2206784.pdf

"Age and Gender Prediction using ConvNet ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. pph763-h766, June-2022, Available at : http://www.jetir.org/papers/JETIR2206784.pdf