Is there implicit limit for DNN input size of OpenCV Android?

I trained a Caffe model which does NOT specify input sizes. Then I ran it on Android using OpenCV. The code is like below.

private void runEntireImageTest(Mat inY) {
    float scaleFactor = 1.0f / 255.0f;
    Scalar mean = new Scalar(0);
    Mat resized = new Mat();

    // (550, 441) runs OK. (smaller sized runs also fine)
    // (551, 441), (550, 442) crash.
    // (441, 550) crashes

    Imgproc.resize(inY, resized, new Size(550, 441));
    Mat segBlob = Dnn.blobFromImage(resized, scaleFactor, resized.size(), mean, false, false);
    mNet.setInput(segBlob);

    // if input size is above some value, crash will happen here
    Mat lastLayer = mNet.forward();
    Mat outY = lastLayer.reshape(1, 1);
}

As it is written in the comment, there seems to be some intrinsic, or implicit limitation for the input size. (550, 441) ran okay, but (551, 441) will cause SIGSEGV:

A/libc: Fatal signal 11 (SIGSEGV), code 1, fault addr 0x6d494bd744 in tid 19693 (myappname), pid 19661 (myappname)

I think it's not a memory problem because (550, 441) runs fine but (441, 550) will crash. What is the cause of this problem?