We　propose　a　novel　LBCNN　model　with　AM　Softmax　based　on　bilinear　CNN　(BCNN)　and　AM　Softmax　loss　function,　which　can　better　fit　fine-grained　birds　recognition　tasks.　There　are　mainly　two　contributions.　Firstly,　in　order　to　reduce　the　model　size　and　recognition　time,　we　design　a　lightweight　BCNN　model　to　reduce　the　parameters.　We　replace　original　VGG16　backbone　with　MobileNet　structure　which　decomposes　the　convolution　operation　into　two　smaller　operations:　depthwise　revolution　and　pointwise　revolution.　Secondly,　to　make　up　for　the　decrease　in　accuracy,　we　introduce　the　Additive　Margin　Softmax　(AM　Softmax)　loss　function　to　enhance　the　discrimination　ability.　By　comprehensive　discussion　of　the　influence　of　different　parameter　settings　and　different　loss　functions,　we　test　the　proposed　lightweight　BCNN　on　the　bird　dataset　CUB-200-2011.　Experimental　results　demonstrate　that　the　proposed　model　can　achieve　comparable　results　with　much　fewer　parameters.　©　2022　SPIE.